In a modern information processing environment, transactional data is often generated in the course of normal operations. With modern technology providing seemingly ever increasing storage capacity and processing resources, such transactional data has the potential to become large and cumbersome, as additional information and audit trail capability is sought. In a storage area network (SAN), for example, a management application generates transactions corresponding to quantitative metrics such as data storage used, storage available, frequency of access, usable capacity, and other statistical information. The statistical information is valuable from a diagnostic and maintenance perspective for various purposes, such as to identify areas of potential backlog, pinpoint performance shortfalls, and for trending analysis to map future demands.
Relational databases have gained popularity for storing such transactional data gathered from an information processing system. More recently, so-called multidimensional databases have provided a mechanism for storing and querying vast amounts of transactional data according to many attributes, or dimensions, such as time, location, product, department, and combinations, permutations, and/or subdivisions of these. While flexible, such multidimensional databases, also known as OnLine Analytical Processing (OLAP) systems, tend to be computation and storage intensive. A modern OLAP system has the potential to generate huge quantities of queryable data, and enables complex queries that require substantial computational resources.
In OLAP systems, as in relational databases (often the underlying storage mechanism in OLAP systems), data is stored in tables having associations to other tables. Report queries are processed by performing a join operation which traverses the associations between tables. However, the processing required is exponentially proportional to the number of entries in the tables. Accordingly, complex multidimensional queries tend to rapidly consume processing power, particularly when many tables are traversed to process the query. Accordingly, the report queries may create contention with the ongoing data gathering operations for the database that they interrogate. In a storage area network, where access to storage arrays is paramount, it is highly detrimental for the transactional processing of the management application to compete with or impede access to the storage arrays.